Cell shapes decode molecular phenotypes in image-based spatial proteomics

Area of Science:

• Cell Biology
• Biophysics
• Proteomics
• Bioinformatics

Background:

• Cellular and tissue diversity arises from basic cell shapes and biophysical constraints on cytoskeletal organization.
• Cellular geometry is linked to biological processes like polarity, signaling, and morphogenesis.
• The relationship between the entire proteome and cell shape is not well understood.

Purpose of the Study:

• To perform an integrated analysis of organelle, pathway, and single protein levels in association with a 2D cellular shapespace.
• To understand the orchestration of the whole proteome in relation to cell shape.
• To analyze protein spatial localization shifts under drug perturbation using a shape-defined coordinate framework.

Main Methods:

• Utilized over 1 million images of single cells from the Human Protein Atlas database.
• Analyzed 11,998 proteins across 10 cell lines.
• Integrated analysis of organelle, pathway, and single protein levels within a 2D cellular shapespace.

Main Results:

• Cell and nuclear shapes form a shared continuum across cell lines.
• Subcellular organelle topology varies by cell line but is robust within each cell line's shapespace.
• Cells of different shapes in the same cell cycle phase may prepare for different fates; many non-cell cycle proteins show shape-based abundance variation.

Conclusions:

• Cell shape is a critical determinant of proteome organization and cellular function.
• Protein localization and abundance are significantly influenced by cell geometry.
• A shape-based coordinate framework enables analysis of drug perturbation effects on protein localization.